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--- |
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license: mit |
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base_model: microsoft/Phi-3-mini-4k-instruct |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: PHI30515HMA1H |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# PHI30515HMA1H |
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This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0747 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_steps: 80 |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 7.2832 | 0.09 | 10 | 2.7337 | |
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| 1.7648 | 0.18 | 20 | 0.3745 | |
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| 0.3839 | 0.27 | 30 | 0.2589 | |
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| 0.3285 | 0.36 | 40 | 0.2520 | |
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| 0.3202 | 0.45 | 50 | 0.2229 | |
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| 0.6502 | 0.54 | 60 | 0.2693 | |
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| 0.3048 | 0.63 | 70 | 0.1647 | |
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| 0.2068 | 0.73 | 80 | 0.1318 | |
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| 0.1411 | 0.82 | 90 | 0.1621 | |
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| 0.1775 | 0.91 | 100 | 0.0975 | |
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| 0.1835 | 1.0 | 110 | 0.0954 | |
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| 0.1014 | 1.09 | 120 | 0.0876 | |
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| 0.1148 | 1.18 | 130 | 0.0976 | |
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| 0.1506 | 1.27 | 140 | 0.0760 | |
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| 0.128 | 1.36 | 150 | 0.0750 | |
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| 0.0883 | 1.45 | 160 | 0.0736 | |
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| 0.0913 | 1.54 | 170 | 0.0692 | |
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| 0.0795 | 1.63 | 180 | 0.0681 | |
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| 0.0927 | 1.72 | 190 | 0.0669 | |
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| 0.087 | 1.81 | 200 | 0.0667 | |
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| 0.0606 | 1.9 | 210 | 0.0682 | |
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| 0.0627 | 1.99 | 220 | 0.0679 | |
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| 0.0441 | 2.08 | 230 | 0.0705 | |
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| 0.0543 | 2.18 | 240 | 0.0813 | |
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| 0.0413 | 2.27 | 250 | 0.0839 | |
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| 0.0414 | 2.36 | 260 | 0.0775 | |
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| 0.0462 | 2.45 | 270 | 0.0756 | |
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| 0.0411 | 2.54 | 280 | 0.0763 | |
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| 0.0392 | 2.63 | 290 | 0.0768 | |
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| 0.0407 | 2.72 | 300 | 0.0771 | |
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| 0.0508 | 2.81 | 310 | 0.0755 | |
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| 0.0577 | 2.9 | 320 | 0.0746 | |
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| 0.0431 | 2.99 | 330 | 0.0747 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.0 |
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